app.py

import streamlit as st
from transformers import pipeline
from PIL import Image
from datasets import load_dataset, Image, list_datasets
from PIL import Image

MODELS = [
            "google/vit-base-patch16-224", #Classifição geral
            "nateraw/vit-age-classifier" #Classifição de idade
]
MAX_N_LABELS = 5



def main():
    st.title("Bulk Image Classification")
    st.markdown("This app uses several 🤗 models to classify images stored in 🤗 datasets.")
    st.write("Soon we will have a dataset template")
    st.write("**Soon we will have dataset selector**")   
    st.text("Select a model to use:")
    st.get_option("model", MODELS)
    dataset = load_dataset("Nunt/testedata","testedata_readme")          
    st.markdown("The models available are:")
    st.markdown("**PUT IT HERE**")
    
    
    dataset = load_dataset("Nunt/testedata","testedata_readme")
    
    
    

if __name__ == "__main__":
    main()